Score a text corpus based on the Okapi BM25 algorithm

A simple wrapper around the BM25 class.

Usage

bm25_score(data, query, lang = NULL, k1 = 1.2, b = 0.75)

Arguments

data

text data, a vector of strings. Note any preprocessing steps (tolower, removing stopwords etc) need to have taken place before this!

query

the term to search for, note all preprocessing that was applied to the text corpus initially needs to be already performed on the term, e.g., tolower, removing stopwords etc

lang

language of the data, see self$available_languages(), can also be "detect" to automatically detect the language, default is "detect"

k1

k1 parameter of BM25, default is 1.2

b

b parameter of BM25, default is 0.75

Value

a numeric vector of the BM25 scores, note higher values are showing a higher relevance of the text to the query

See also

BM25

Examples

corpus <- c(
 "The rabbit munched the orange carrot.",
 "The snake hugged the green lizard.",
 "The hedgehog impaled the orange orange.",
 "The squirrel buried the brown nut."
)
scores <- bm25_score(data = corpus, query = "orange")
data.frame(text = corpus, scores_orange = scores)
#>                                      text scores_orange
#> 1   The rabbit munched the orange carrot.     0.3566750
#> 2      The snake hugged the green lizard.     0.0000000
#> 3 The hedgehog impaled the orange orange.     0.4904281
#> 4      The squirrel buried the brown nut.     0.0000000